Nosocomial infections place a substantial burden on health care systems and represent one of the major issues in current public health, requiring notable efforts for its prevention. Understanding the dynamics of infection transmission in a hospital setting is essential for tailoring interventions and predicting the spread among individuals. Mathematical models need to be informed with accurate data on contacts among individuals. We used wearable active Radio-Frequency Identification Devices (RFID) to detect face-to-face contacts among individuals with a spatial resolution of about 1.5 meters, and a time resolution of 20 seconds. The study was conducted in a general pediatrics hospital ward, during a one-week period, and included 119 participants, with 51 health care workers, 37 patients, and 31 caregivers. Nearly 16,000 contacts were recorded during the study period, with a median of approximately 20 contacts per participants per day. Overall, 25% of the contacts involved a ward assistant, 23% a nurse, 22% a patient, 22% a caregiver, and 8% a physician. The majority of contacts were of brief duration, but long and frequent contacts especially between patients and caregivers were also found. In the setting under study, caregivers do not represent a significant potential for infection spread to a large number of individuals, as their interactions mainly involve the corresponding patient. Nurses would deserve priority in prevention strategies due to their central role in the potential propagation paths of infections. Our study shows the feasibility of accurate and reproducible measures of the pattern of contacts in a hospital setting. The obtained results are particularly useful for the study of the spread of respiratory infections, for monitoring critical patterns, and for setting up tailored prevention strategies. Proximity-sensing technology should be considered as a valuable tool for measuring such patterns and evaluating nosocomial prevention strategies in specific settings.

Background: The use of the Internet for searching and sharing health information and for health care interactions may have a great potential for families of children affected with rare diseases. We conducted an online survey among Italian families of patients with rare diseases with the objective to describe their Internet user profile, and to explore how Internet use affects their health decisions. Methods: All members of UNIAMIO FIMR, a federation of associations of patients with rare diseases, were invited via mail to participate in an online questionnaire including questions on socio-demographic and clinical information, Internet use with a specific focus on health, and impact of web information on health behaviors. Logistic regression models were used to explore the effect of socio-demographic variables and Internet user profile on dependent variables representing the impact of web information on health behaviors. Multiple imputation by chained equations was applied. Results: A total of 516 parents of patients with rare diseases completed the online questionnaire. Mean age was 43 years. 87% of respondents accessed the Internet daily, 40% through their smartphones. 99% had an email account, 71% had a Facebook account. 66% participate in an online forum on health. 99% searched for information on disease characteristics, 93% on therapy, 89% on diagnosis, 63% on alternative therapies, 62% on nutrition and 54% on future pregnancies. 82% stated that web information increased comprehension of the disease, 65% that it improved management of the disease. For 52% web information increased his or her anxiety. 62% recognized diagnosis, 69% discussed online information with their physician. People participating in forums more frequently stated that Internet information was useful for recognizing their child’s disease (OR 1.68; 95%CI 1.08-2.63) and for improving its management (OR 1.77; 95%CI 1.11-2.81). Conclusion: Italian parents of patients with rare diseases are active Internet users, engaged in information search and in online communities. Physicians, health care facilities and health agencies have a great opportunity to engage in online interactions for empowering families of patients of children affected with rare diseases.

Twitter has the potential to be a timely and cost-effective source of data for syndromic surveillance. When speaking of an illness, Twitter users often report a combination of symptoms, rather than a suspected or final diagnosis, using naïve, everyday language. We developed a minimally trained algorithm that exploits the abundance of health-related web pages to identify all jargon expressions related to a specific technical term. We then translated an influenza case definition into a Boolean query, each symptom being described by a technical term and all related jargon expressions, as identified by the algorithm. Subsequently, we monitored all tweets that reported a combination of symptoms satisfying the case definition query. In order to geolocalize messages, we defined 3 localization strategies based on codes associated with each tweet. We found a high correlation coefficient between the trend of our influenza-positive tweets and ILI trends identified by US traditional surveillance systems.

Background: Viral respiratory tract infections (VRI) are a major reason for hospitalization in children younger than 5 years. A case control study was conducted to investigate the potential role of breastfeeding in protecting children <1 year of age from VRI. Methods: Patients admitted for a respiratory tract infections routinely underwent a nasopharyngeal aspirate, which was tested with an RT-PCR for 14 respiratory viruses. Hospitalized infants positive for viruses were enrolled as cases; healthy controls were enrolled among patients admitted for ultrasound hip screening. The effect of breastfeeding on pertussis was investigated through multivariable analysis. Results: We enrolled a total of 496 patients: 238 cases and 258 healthy controls. Among cases, eighty-six patients (36.1%) had a rinovirus, 78 (32.8%) an RSV, 22 (9.2%) an adenovirus, and 37 (15.5%) a coinfections with multiple viruses. The number of households was significantly higher in cases (mean in cases 4.5; mean 3.7 in controls, p < 0.001) and the proportion of infants having siblings (79% in cases vs. 43% in controls, p < 0.001). Proportion of smoking mothers was higher in cases than in controls (21.4 vs. 10.1%, p = 0.001). Among cases 44.5% were exclusively breastfed at symptoms onset vs. 48.8% of healthy controls. According to the multivariable analysis, being exclusively breastfed at symptom onset was associated with a higher risk of viral respiratory infection (3.7; 95% CI 1.64–8.41), however a longer breastfeeding duration was protective (OR 0.98; 95% CI 0.97–0.99). Also having at least one sibling was associated to a higher risk (OR 3.6; 95% CI 2.14–5.92) as well as having a smoking mother (OR 2.6; 95% CI 1.33–4.89). Conclusions: Breastfeeding remains a mainstay of prevention for numerous diseases and its protective role increases with duration. However, being breastfed when mothers carry a respiratory infection may increase the risk of transmission, acting as a proxy for closer contacts. In future studies, potential confounding variables as pattern of contacts with other individuals, should be taken into account.